Healthcare protocol change evaluation

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National Immunization Program: H. Gay Allen, M. Bernier, Ph. D; Nancy Koughan, D. Roush, M. Louis University, St. Louis, Missouri. Paul Etkind, Dr. Fletcher, D. Friedman, Ph. Hopkins, M. MacDonald, Ph. Mann, D. Potjaman, M. Salive, M. The purpose of evaluating public health surveillance systems is to ensure that problems of public health importance are being monitored efficiently and effectively.

CDC's Guidelines for Evaluating Surveillance Systems are being updated to address the need for a the integration of surveillance and health information systems, b the establishment of data standards, c the electronic exchange of health data, and d changes in the objectives of public health surveillance to facilitate the response of public health to emerging health threats e.

This report provides updated guidelines for evaluating surveillance systems based on CDC's Framework for Program Evaluation in Public Health , research and discussion of concerns related to public health surveillance systems, and comments received from the public health community. The guidelines in this report describe many tasks and related activities that can be applied to public health surveillance systems.

For example, CDC, with the collaboration of state and local health departments, is implementing the National Electronic Disease Surveillance System NEDSS to better manage and enhance the large number of current surveillance systems and allow the public health community to respond more quickly to public health threats e.

When NEDSS is completed, it will electronically integrate and link together several types of surveillance systems with the use of standard data formats; a communications infrastructure built on principles of public health informatics; and agreements on data access, sharing, and confidentiality. In addition, the Health Insurance Portability and Accountability Act of HIPAA mandates that the United States adopt national uniform standards for electronic transactions related to health insurance enrollment and eligibility, health-care encounters, and health insurance claims; for identifiers for health-care providers, payers and individuals, as well as code sets and classification systems used in these transactions; and for security of these transactions 3.

The electronic exchange of health data inherently involves the protection of patient privacy. Based on CDC's Framework for Program Evaluation in Public Health 4 , research and discussion of concerns related to public health surveillance systems, and comments received from the public health community, this report provides updated guidelines for evaluating public health surveillance systems.

Data disseminated by a public health surveillance system can be used for immediate public health action, program planning and evaluation, and formulating research hypotheses. For example, data from a public health surveillance system can be used to guide immediate action for cases of public health importance; measure the burden of a disease or other health-related event , including changes in related factors, the identification of populations at high risk, and the identification of new or emerging health concerns; monitor trends in the burden of a disease or other health-related event , including the detection of epidemics outbreaks and pandemics; guide the planning, implementation, and evaluation of programs to prevent and control disease, injury, or adverse exposure; evaluate public policy; detect changes in health practices and the effects of these changes; prioritize the allocation of health resources; describe the clinical course of disease; and provide a basis for epidemiologic research.

Public health surveillance activities are generally authorized by legislators and carried out by public health officials. Public health surveillance systems have been developed to address a range of public health needs.

In addition, public health information systems have been defined to include a variety of data sources essential to public health action and are often used for surveillance 8. These systems vary from a simple system collecting data from a single source, to electronic systems that receive data from many sources in multiple formats, to complex surveys. The number and variety of systems will likely increase with advances in electronic data interchange and integration of data, which will also heighten the importance of patient privacy, data confidentiality, and system security.

Variety might also increase with the range of health-related events under surveillance. In these guidelines, the term "health-related event" refers to any subject related to a public health surveillance system.

For example, a health-related event could include infectious, chronic, or zoonotic diseases; injuries; exposures to toxic substances; health promoting or damaging behaviors; and other surveilled events associated with public health action. Public health surveillance systems should be evaluated periodically, and the evaluation should include recommendations for improving quality, efficiency, and usefulness. The goal of these guidelines is to organize the evaluation of a public health surveillance system.

Broad topics are outlined into which program-specific qualities can be integrated. Evaluation of a public health surveillance system focuses on how well the system operates to meet its purpose and objectives.

The evaluation of public health surveillance systems should involve an assessment of system attributes, including simplicity, flexibility, data quality, acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability. With the continuing advancement of technology and the importance of information architecture and related concerns, inherent in these attributes are certain public health informatics concerns for public health surveillance systems.

These concerns include comparable hardware and software, standard user interface, standard data format and coding, appropriate quality checks, and adherence to confidentiality and security standards 9. Because public health surveillance systems vary in methods, scope, purpose, and objectives, attributes that are important to one system might be less important to another.

A public health surveillance system should emphasize those attributes that are most important for the objectives of the system. Efforts to improve certain attributes e. An evaluation of the public health surveillance system must therefore consider those attributes that are of the highest priority for a given system and its objectives.

Considering the attributes that are of the highest priority, the guidelines in this report describe many tasks and related activities that can be applied in the evaluation of public health surveillance systems, with the understanding that all activities under the tasks might not be appropriate for all systems.

This report begins with descriptions of each of the tasks involved in evaluating a public health surveillance system. These tasks are adapted from the steps in program evaluation in the Framework for Program Evaluation in Public Health 4 as well as from the elements in the original guidelines for evaluating surveillance systems 1.

The report concludes with a summary statement regarding evaluating surveillance systems. A checklist that can be detached or photocopied and used when the evaluation is implemented is also included Appendix A. To assess the quality of the evaluation activities, relevant standards are provided for each of the tasks for evaluating a public health surveillance system Appendix B.

These standards are adapted from the standards for effective evaluation i. Because all activities under the evaluation tasks might not be appropriate for all systems, only those standards that are appropriate to an evaluation should be used. Stakeholders can provide input to ensure that the evaluation of a public health surveillance system addresses appropriate questions and assesses pertinent attributes and that its findings will be acceptable and useful.

In that context, we define stakeholders as those persons or organizations who use data for the promotion of healthy lifestyles and the prevention and control of disease, injury, or adverse exposure.

Those stakeholders who might be interested in defining questions to be addressed by the surveillance system evaluation and subsequently using the findings from it are public health practitioners; health-care providers; data providers and users; representatives of affected communities; governments at the local, state, and federal levels; and professional and private nonprofit organizations.

Activities Describe the public health importance of the health-related event under surveillance. Describe the purpose and operation of the system. Describe the resources used to operate the system.

To construct a balanced and reliable description of the system, multiple sources of information might be needed. The description of the system can be improved by consulting with a variety of persons involved with the system and by checking reported descriptions of the system against direct observation. The public health importance of a health-related event and the need to have that event under surveillance can be described in several ways.

Health-related events that affect many persons or that require large expenditures of resources are of public health importance. However, health-related events that affect few persons might also be important, especially if the events cluster in time and place e.

In other instances, public concerns might focus attention on a particular health-related event, creating or heightening the importance of an evaluation. Diseases that are now rare because of successful control measures might be perceived as unimportant, but their level of importance should be assessed as a possible sentinel health-related event or for their potential to reemerge.

Finally, the public health importance of a health-related event is influenced by its level of preventability Parameters for measuring the importance of a health-related eventand therefore the public health surveillance system with which it is monitoredcan include 7 indices of frequency e.

Efforts have been made to provide summary measures of population health status that can be used to make comparative assessments of the health needs of populations In addition, attempts have been made to quantify the public health importance of various diseases and other health-related events. In a study that describes such an approach, a score was used that takes into account agespecific morbidity and mortality rates as well as healthcare costs Another study used a model that ranks public health concerns according to size, urgency, severity of the problem, economic loss, effect on others, effectiveness, propriety, economics, acceptability, legality of solutions, and availability of resources Preventability can be defined at several levels, including primary prevention preventing the occurrence of disease or other health-related event , secondary prevention early detection and intervention with the aim of reversing, halting, or at least retarding the progress of a condition , and tertiary prevention minimizing the effects of disease and disability among persons already ill.

For infectious diseases, preventability can also be described as reducing the secondary attack rate or the number of cases transmitted to contacts of the primary case. From the perspective of surveillance, preventability reflects the potential for effective public health intervention at any of these levels. Methods for describing the operation of the public health surveillance system include List the purpose and objectives of the system. Describe the planned uses of the data from the system.

Describe the health-related event under surveillance, including the case definition for each specific condition. Cite any legal authority for the data collection. Describe where in the organization s the system resides, including the context e. Describe the level of integration with other systems, if appropriate. Draw a flow chart of the system. Describe the components of the system. For example What is the population under surveillance?

Does the system comply with applicable standards for data formats and coding schemes? If not, why? What is the policy and procedure for releasing data? Do these procedures comply with applicable federal and state statutes and regulations? The purpose of the system indicates why the system exists, whereas its objectives relate to how the data are used for public health action.

The objectives of a public health surveillance system, for example, might address immediate public health action, program planning and evaluation, and formation of research hypotheses see Background. The purpose and objectives of the system, including the planned uses of its data, establish a frame of reference for evaluating specific components. A public health surveillance system is dependent on a clear case definition for the health-related event under surveillance 7. The case definition of a health-related event can include clinical manifestations i.

The use of a standard case definition increases the specificity of reporting and improves the comparability of the health-related event reported from different sources of data, including geographic areas.

Case definitions might exist for a variety of health-related events under surveillance, including diseases, injuries, adverse exposures, and risk factor or protective behaviors.

When possible, a public health surveillance system should use an established case definition, and if it does not, an explanation should be provided. The evaluation should assess how well the public health surveillance system is integrated with other surveillance and health information systems e. Streamlining related systems into an integrated public health surveillance network enables individual systems to meet specific data collection needs while avoiding the duplication of effort and lack of standardization that can arise from independent systems An integrated system can address comorbidity concerns e.

When CDC's NEDSS is completed, it will electronically integrate and link together several types of surveillance activities and facilitate more accurate and timely reporting of disease information to CDC and state and local health departments 2.

CSTE has organized professional discussion among practicing public health epidemiologists at state and federal public health agencies. CSTE has also proposed a national public health surveillance system to serve as a basis for local and state public health agencies to a prioritize surveillance and health information activities and b advocate for necessary resources for public health agencies at all levels This national public health system would be a conceptual framework and virtual surveillance system that incorporates both existing and new surveillance systems for health-related events and their determinants.

Listing the discrete steps that are taken in processing the health-event reports by the system and then depicting these steps in a flow chart is often useful.

An example of a simplified flow chart for a generic public health surveillance system is included in this report Figure 1. The mandates and business processes of the lead agency that operates the system and the participation of other agencies could be included in this chart. The architecture and data flow of the system can also be depicted in the chart 20, A chart of architecture and data flow should be sufficiently detailed to explain all of the functions of the system, including average times between steps and data transfers.

The description of the components of the public health surveillance system could include discussions related to public health informatics concerns, including comparable hardware and software, standard user interface, standard data format and coding, appropriate quality checks, and adherence to confidentiality and security standards 9. For example, comparable hardware and software, standard user interface, and standard data format and coding facilitate efficient data exchange, and a set of common data elements are important for effectively matching data within the system or to other systems.

To document the information needs of public health, CDC, in collaboration with state and local health departments, is developing the Public Health Conceptual Data Model to a establish data standards for public health, including data definitions, component structures e. In addition, the description of the system's data management might address who is editing the data, how and at what levels the data are edited, and what checks are in place to ensure data quality.

In response to HIPAA mandates, various standard development organizations and terminology and coding groups are working collaboratively to harmonize their separate systems For example, both the Accredited Standards Committee X12 24 , which has dealt principally with standards for health insurance transactions, and Health Level Seven HL7 25 , which has dealt with standards for clinical messaging and exchange of clinical information with health-care organizations e.

In the area of classification and coding of diseases and other medical terms, the National Library of Medicine has traditionally provided the Unified Medical Language System, a metathesaurus for clinical coding systems that allows terms in one coding system to be mapped to another The passage of HIPAA and the anticipated adoption of standards for electronic medical records have increased efforts directed toward the integration of clinical terminologies 23 e.

The data analysis description might indicate who analyzes the data, how they are analyzed, and how often. This description could also address how the system ensures that appropriate scientific methods are used to analyze the data.

The public health surveillance system should operate in a manner that allows effective dissemination of health data so that decision makers at all levels can readily understand the implications of the information 7. The audiences for health data and information can include public health practitioners, health-care providers, members of affected communities, professional and voluntary organizations, policymakers, the press, and the general public.

In conducting surveillance, public health agencies are authorized to collect personal health data about persons and thus have an obligation to protect against inappropriate use or release of that data.

The protection of patient privacy recognition of a person's right not to share information about him or herself , data confidentiality assurance of authorized data sharing , and system security assurance of authorized system access is essential to maintaining the credibility of any surveillance system.

This protection must ensure that data in a surveillance system regarding a person's health status are shared only with authorized persons. Physical, administrative, operational, and computer safeguards for securing the system and protecting its data must allow authorized access while denying access by unauthorized users.

A related concern in protecting health data is data release, including procedures for releasing record-level data; aggregate tabular data; and data in computer-based, interactive query systems. Even though personal identifiers are removed before data are released, the removal of these identifiers might not be a sufficient safeguard for sharing health data.

For example, the inclusion of demographic information in a line-listed data file for a small number of cases could lead to indirect identification of a person even though personal identifiers were not provided. Standards for the privacy of individually identifiable health data have been proposed in response to HIPAA 3.

A model state law has been composed to address privacy, confidentiality, and security concerns arising from the acquisition, use, disclosure, and storage of health information by public health agencies at the state and local levels In addition, the Federal Committee on Statistical Methodology's series of Statistical Policy Working Papers includes reviews of statistical methods used by federal agencies and their contractors that release statistical tables or microdata files that are collected from persons, businesses, or other units under a pledge of confidentiality.

These working papers contain basic statistical methods to limit disclosure e. A public health surveillance system might be legally required to participate in a records management program. Records can consist of a variety of materials e. The proper management of these records prevents a "loss of memory" or "cluttered memory" for the agency that operates the system, and enhances the system's ability to meet its objectives.

In this report, the methods for assessing resources cover only those resources directly required to operate a public health surveillance system. These resources are sometimes referred to as "direct costs" and include the personnel and financial resources expended in operating the system. In describing these resources consider the following: Funding source s : Specify the source of funding for the surveillance system. In the United States, public health surveillance often results from a collaboration among federal, state, and local governments.

Personnel requirements: Estimate the time it takes to operate the system, including the collection, editing, analysis, and dissemination of data e. These measures can be converted to dollar estimates by multiplying the persontime by appropriate salary and benefit costs.

Other resources: Determine the cost of other resources, including travel, training, supplies, computer and other equipment, and related services e. When appropriate, the description of the system's resources should consider all levels of the public health system, from the local healthcare provider to municipal, county, state, and federal health agencies. Resource estimation for public health surveillance systems have been implemented in Vermont Table 1 and Kentucky Table 2.

Resource Estimation in Vermont. Two methods of collecting public health surveillance data in Vermont were compared The passive system was already in place and consisted of unsolicited reports of notifiable diseases to the district offices or state health department. The active system was implemented in a probability sample of physician practices. Each week, a health department employee called these practitioners to solicit reports of selected notifiable diseases.

In comparing the two systems, an attempt was made to estimate their costs. The estimates of direct expenses were computed for the public health surveillance systems Table 1. Resource Estimation in Kentucky. Another example of resource estimation was provided by an assessment of the costs of a public health surveillance system involving the active solicitation of case reports of type A hepatitis in Kentucky Table 2 Nine more cases were found through this system than would have been found through the passive surveillance system, and an estimated seven hepatitis cases were prevented through administering prophylaxis to the contacts of the nine casepatients.

This approach to assessing resources includes only those personnel and material resources required for the operation of surveillance and excludes a broader definition of costs that might be considered in a more comprehensive evaluation. For example, the assessment of resources could include the estimation of indirect costs e. The assessment of the system's operational resources should not be done in isolation of the program or initiative that relies on the public health surveillance system.

A more formal economic evaluation of the system i. For some surveillance systems, however, a more realistic approach would be to judge costs based on the objectives and usefulness of the system.

The direction and process of the evaluation must be focused to ensure that time and resources are used as efficiently as possible. Focusing the evaluation design for a public health surveillance system involves determining the specific purpose of the evaluation e. Depending on the specific purpose of the evaluation, its design could be straightforward or complex. An effective evaluation design is contingent upon a its specific purpose being understood by all of the stakeholders in the evaluation and b persons who need to know the findings and recommendations of the design being committed to using the information generated from it.

In addition, when multiple stakeholders are involved, agreements that clarify roles and responsibilities might need to be established among those who are implementing the evaluation. Standards for assessing how the public health surveillance system performs establish what the system must accomplish to be considered successful in meeting its objectives.

These standards specify, for example, what levels of usefulness and simplicity are relevant for the system, given its objectives. Task D. Activities Indicate the level of usefulness by describing the actions taken as a result of analysis and interpretation of the data from the public health surveillance system. Characterize the entities that have used the data to make decisions and take actions.

List other anticipated uses of the data. Describe each of the following system attributes: Simplicity Flexibility Data quality Acceptability Sensitivity Predictive value positive Representativeness Timeliness Stability Discussion. Public health informatics concerns for public health surveillance systems see Task B. Evidence of the system's performance must be viewed as credible. For example, the gathered evidence must be reliable, valid, and informative for its intended use.

Many potential sources of evidence regarding the system's performance exist, including consultations with physicians, epidemiologists, statisticians, behavioral scientists, public health practitioners, laboratory directors, program managers, data providers, and data users.

A public health surveillance system is useful if it contributes to the prevention and control of adverse health-related events, including an improved understanding of the public health implications of such events.

A public health surveillance system can also be useful if it helps to determine that an adverse health-related event previously thought to be unimportant is actually important. In addition, data from a surveillance system can be useful in contributing to performance measures 37 , including health indicators 38 that are used in needs assessments and accountability systems.

An assessment of the usefulness of a public health surveillance system should begin with a review of the objectives of the system and should consider the system's effect on policy decisions and disease-control programs. Depending on the objectives of a particular surveillance system, the system might be considered useful if it satisfactorily addresses at least one of the following questions. Does the system detect diseases, injuries, or adverse or protective exposures of public importance in a timely way to permit accurate diagnosis or identification, prevention or treatment, and handling of contacts when appropriate?

A survey of persons who use data from the system might be helpful in gathering evidence regarding the usefulness of the system. The survey could be done either formally with standard methodology or informally.

Usefulness might be affected by all the attributes of a public health surveillance system see Task D. For example, increased sensitivity might afford a greater opportunity for identifying outbreaks and understanding the natural course of an adverse health-related event in the population under surveillance.

Improved timeliness allows control and prevention activities to be initiated earlier. Increased predictive value positive enables public health officials to more accurately focus resources for control and prevention measures. A representative surveillance system will better characterize the epidemiologic characteristics of a health-related event in a defined population.

Public health surveillance systems that are simple, flexible, acceptable, and stable will likely be more complete and useful for public health action. The simplicity of a public health surveillance system refers to both its structure and ease of operation. Surveillance systems should be as simple as possible while still meeting their objectives.

A chart describing the flow of data and the lines of response in a surveillance system can help assess the simplicity or complexity of a surveillance system. A simplified flow chart for a generic surveillance system is included in this report Figure 1.

The following measures see Task B. Thinking of the simplicity of a public health surveillance system from the design perspective might be useful. An example of a system that is simple in design is one with a case definition that is easy to apply i. A more complex system might involve some of the following: special or follow-up laboratory tests to confirm the case; investigation of the case, including telephone contact or a home visit by public health personnel to collect detailed information; multiple levels of reporting e.

Simplicity is closely related to acceptance and timeliness. Simplicity also affects the amount of resources required to operate the system. A flexible public health surveillance system can adapt to changing information needs or operating conditions with little additional time, personnel, or allocated funds. Flexible systems can accommodate, for example, new health-related events, changes in case definitions or technology, and variations in funding or reporting sources.

In addition, systems that use standard data formats e. Flexibility is probably best evaluated retrospectively by observing how a system has responded to a new demand.

Conducted in collaboration with state health departments, BRFSS is an ongoing sample survey that gathers and reports state-level prevalence data on health behaviors related to the leading preventable causes of death as well as data on preventive health practices. The system permits states to add questions of their own design to the BRFSS questionnaire but is uniform enough to allow state-to-state comparisons for certain questions.

These state-specific questions can address emergent and locally important health concerns. In addition, states can stratify their BRFSS samples to estimate prevalence data for regions or counties within their respective states. Unless efforts have been made to adapt the public health surveillance system to another disease or other health-related event , a revised case definition, additional data sources, new information technology, or changes in funding, assessing the flexibility of that system might be difficult.

In the absence of practical experience, the design and workings of a system can be examined. Simpler systems might be more flexible i. Data quality reflects the completeness and validity of the data recorded in the public health surveillance system. Examining the percentage of "unknown" or "blank" responses to items on surveillance forms is a straightforward and easy measure of data quality. Data of high quality will have low percentages of such responses. However, a full assessment of the completeness and validity of the system's data might require a special study.

Data values recorded in the surveillance system can be compared to "true" values through, for example, a review of sampled data 40 , a special record linkage 41 , or patient interview In addition, the calculation of sensitivity Task D. Quality of data is influenced by the performance of the screening and diagnostic tests i. A review of these facets of a public health surveillance system provides an indirect measure of data quality.

Most surveillance systems rely on more than simple case counts. Data commonly collected include the demographic characteristics of affected persons, details about the health-related event, and the presence or absence of potential risk factors.

The quality of these data depends on their completeness and validity. The acceptability see Task D. With data of high quality, the system can be accepted by those who participate in it. In addition, the system can accurately represent the health-related event under surveillance.

Acceptability reflects the willingness of persons and organizations to participate in the surveillance system. Acceptability refers to the willingness of persons in the sponsoring agency that operates the system and persons outside the sponsoring agency e. To assess acceptability, the points of interaction between the system and its participants must be considered Figure 1 , including persons with the health-related event and those reporting cases. Some of these measures might be obtained from a review of surveillance report forms, whereas others would require special studies or surveys.

Acceptability is a largely subjective attribute that encompasses the willingness of persons on whom the public health surveillance system depends to provide accurate, consistent, complete, and timely data. Some factors influencing the acceptability of a particular system are the public health importance of the health-related event; acknowledgment by the system of the person's contribution; dissemination of aggregate data back to reporting sources and interested parties; responsiveness of the system to suggestions or comments; burden on time relative to available time; ease and cost of data reporting; federal and state statutory assurance of privacy and confidentiality; the ability of the system to protect privacy and confidentiality; federal and state statute requirements for data collection and case reporting; and participation from the community in which the system operates.

The sensitivity of a surveillance system can be considered on two levels. First, at the level of case reporting, sensitivity refers to the proportion of cases of a disease or other health-related event detected by the surveillance system Second, sensitivity can refer to the ability to detect outbreaks, including the ability to monitor changes in the number of cases over time.

These situations can be extended by analogy to public health surveillance systems that do not fit the traditional disease careprovider model. For example, the sensitivity of a telephonebased surveillance system of morbidity or risk factors is affected by the number of persons who have telephones, who are at home when the call is placed, and who agree to participate; the ability of persons to understand the questions and correctly identify their status; and the willingness of respondents to report their status.

The extent to which these situations are explored depends on the system and on the resources available for assessing sensitivity. Surveillance of vaccine-preventable diseases provides an example of where the detection of outbreaks is a critical concern Approaches that have been recommended for improving sensitivity of reporting vaccine-preventable diseases might be applicable to other health-related events For example, the sensitivity of a system might be improved by conducting active surveillance i.

The capacity for a public health surveillance system to detect outbreaks or other changes in incidence and prevalence might be enhanced substantially if detailed diagnostic tests are included in the system.

For example, the use of molecular subtyping in the surveillance of Escherichia coli OH7 infections in Minnesota enabled the surveillance system to detect outbreaks that would otherwise have gone unrecognized The measurement of the sensitivity of the surveillance system Table 3 requires a collection of or access to data usually external to the system to determine the true frequency of the condition in the population under surveillance 46 and b validation of the data collected by the system.

Examples of data sources used to assess the sensitivity of health information or public health surveillance systems include medical records 47,48 and registries 49, In addition, sensitivity can be assessed through estimations of the total cases in the population under surveillance by using capture-recapture techniques 51, To adequately assess the sensitivity of the public health surveillance system, calculating more than one measurement of the attribute might be necessary.

For example, sensitivity could be determined for the system's data fields, for each data source or for combinations of data sources 48 , for specific conditions under surveillance 53 , or for each of several years The use of a Venn diagram might help depict measurements of sensitivity for combinations of the system's data sources A literature review can be helpful in determining sensitivity measurements for a public health surveillance system The assessment of the sensitivity of each data source, including combinations of data sources, can determine if the elimination of a current data source or if the addition of a new data source would affect the overall surveillance results A public health surveillance system that does not have high sensitivity can still be useful in monitoring trends as long as the sensitivity remains reasonably constant over time.

Questions concerning sensitivity in surveillance systems most commonly arise when changes in the occurrence of a health-related event are noted. Changes in sensitivity can be precipitated by some circumstances e. A search for such "artifacts" is often an initial step in outbreak investigations. Predictive value positive PVP is the proportion of reported cases that actually have the health-related event under surveillance The assessment of sensitivity and of PVP provide different perspectives regarding how well the system is operating.

Depending on the objectives of the public health surveillance system, assessing PVP whenever sensitivity has been assessed might be necessary , In assessing PVP, primary emphasis is placed on the confirmation of cases reported through the surveillance system.

The effect of PVP on the use of public health resources can be considered on two levels. At the level of case detection, PVP affects the amount of resources used for case investigations. For example, in some states, every reported case of type A hepatitis is promptly investigated by a public health nurse, and contacts at risk are referred for prophylactic treatment. A surveillance system with low PVP, and therefore frequent "falsepositive" case reports, would lead to misdirected resources.

At the level of outbreak or epidemic detection, a high rate of erroneous case reports might trigger an inappropriate outbreak investigation.

Therefore, the proportion of epidemics identified by the surveillance system that are true epidemics can be used to assess this attribute. Calculating the PVP might require that records be kept of investigations prompted by information obtained from the public health surveillance system.

At the level of case detection, a record of the number of case investigations completed and the proportion of reported persons who actually had the health-related event under surveillance would allow the calculation of the PVP. At the level of outbreak detection, the review of personnel activity reports, travel records, and telephone logbooks might enable the assessment of PVP. For some surveillance systems, however, a review of data external to the system e. Examples of data sources used to assess the PVP of health information or public health surveillance systems include medical records 48,57 , registries 49,58 , and death certificates To assess the PVP of the system adequately, calculating more than one measurement of the attribute might be necessary.

For example, PVP could be determined for the system's data fields, for each data source or combinations of data sources 48 , or for specific health-related events PVP is important because a low value means that noncases might be investigated, and outbreaks might be identified that are not true but are instead artifacts of the public health surveillance system e. Falsepositive reports can lead to unnecessary interventions, and falsely detected outbreaks can lead to costly investigations and undue concern in the population under surveillance.

A public health surveillance system with a high PVP will lead to fewer misdirected resources. The PVP reflects the sensitivity and specificity of the case definition i. The PVP can improve with increasing specificity of the case definition.

In addition, good communication between the persons who report cases and the receiving agency can lead to an improved PVP. Take, for example, care for patients with low back pain—one of the most common and expensive causes of disability.

One patient might begin care with a primary care physician, while others might start with an orthopedist, a neurologist, or a rheumatologist. What happens next is unpredictable. Patients might be referred to yet another physician or to a physical therapist. They might undergo radiology testing this could happen at any point—even before seeing a physician. Each encounter is separate from the others, and no one coordinates the care.

Duplication of effort, delays, and inefficiency is almost inevitable. Since no one measures patient outcomes, how long the process takes, or how much the care costs, the value of care never improves. The impact on value of IPUs is striking.

Patients with low back pain call one central phone number SPINE , and most can be seen the same day. Those with serious causes of back pain such as a malignancy or an infection are quickly identified and enter a process designed to address the specific diagnosis.

Other patients will require surgery and will enter a process for that. For most patients, however, physical therapy is the most effective next intervention, and their treatment often begins the same day. Rather, it eliminated the chaos by creating a new system in which caregivers work together in an integrated way.

The impact on value has been striking. Better care has actually lowered costs, a point we will return to later. Virginia Mason has also increased revenue through increased productivity, rather than depending on more fee-for-service visits to drive revenue from unneeded or duplicative tests and care. The clinic sees about 2, new patients per year compared with 1, under the old system, and it does so in the same space and with the same number of staff members.

Wherever IPUs exist, we find similar results—faster treatment, better outcomes, lower costs, and, usually, improving market share in the condition. But those results can be achieved only through a restructuring of work. Simply co-locating staff in the same building, or putting up a sign announcing a Center of Excellence or an Institute, will have little impact. IPUs emerged initially in the care for particular medical conditions, such as breast cancer and joint replacement.

Today, condition-based IPUs are proliferating rapidly across many areas of acute and chronic care, from organ transplantation to shoulder care to mental health conditions such as eating disorders.

Porter, Erika A. Pabo, and Thomas H. By its very nature, primary care is holistic, concerned with all the health circumstances and needs of a patient. The complexity of meeting their heterogeneous needs has made value improvement very difficult in primary care—for example, heterogeneous needs make outcomes measurement next to impossible. In primary care, IPUs are multidisciplinary teams organized to serve groups of patients with similar primary and preventive care needs—for example, patients with complex chronic conditions such as diabetes, or disabled elderly patients.

Different patient groups require different teams, different types of services, and even different locations of care. Within each patient group, the appropriate clinical team, preventive services, and education can be put in place to improve value, and results become measureable.

This approach is already starting to be applied to high-risk, high-cost patients through so-called Patient-Centered Medical Homes. But the opportunity to substantially enhance value in primary care is far broader.

At Geisinger Health System, in Pennsylvania, for example, the care for patients with chronic conditions such as diabetes and heart disease involves not only physicians and other clinicians but also pharmacists, who have major responsibility for following and adjusting medications.

The inclusion of pharmacists on teams has resulted in fewer strokes, amputations, emergency department visits, and hospitalizations, and in better performance on other outcomes that matter to patients.

Rapid improvement in any field requires measuring results—a familiar principle in management. Teams improve and excel by tracking progress over time and comparing their performance to that of peers inside and outside their organization. Indeed, rigorous measurement of value outcomes and costs is perhaps the single most important step in improving health care.

Wherever we see systematic measurement of results in health care—no matter what the country—we see those results improve. Yet the reality is that the great majority of health care providers and insurers fail to track either outcomes or costs by medical condition for individual patients.

That surprising truth goes a long way toward explaining why decades of health care reform have not changed the trajectory of value in the system. When outcomes measurement is done, it rarely goes beyond tracking a few areas, such as mortality and safety.

HEDIS the Healthcare Effectiveness Data and Information Set scores consist entirely of process measures as well as easy-to-measure clinical indicators that fall well short of actual outcomes. For diabetes, for example, providers measure the reliability of their LDL cholesterol checks and hemoglobin A1c levels, even though what really matters to patients is whether they are likely to lose their vision, need dialysis, have a heart attack or stroke, or undergo an amputation.

Few health care organizations yet measure how their diabetic patients fare on all the outcomes that matter. The only true measures of quality are the outcomes that matter to patients. And when those outcomes are collected and reported publicly, providers face tremendous pressure—and strong incentives—to improve and to adopt best practices, with resulting improvements in outcomes.

Take, for example, the Fertility Clinic Success Rate and Certification Act of , which mandated that all clinics performing assisted reproductive technology procedures, notably in vitro fertilization, provide their live birth rates and other metrics to the Centers for Disease Control.

After the CDC began publicly reporting those data, in , improvements in the field were rapidly adopted, and success rates for all clinics, large and small, have steadily improved. Since public reporting of clinic performance began, in , in vitro fertilization success rates have climbed steadily across all clinics as process improvements have spread.

Outcomes should be measured by medical condition such as diabetes , not by specialty podiatry or intervention eye examination. The outcomes that matter to patients for a particular medical condition fall into three tiers. Tier 1 involves the health status achieved. In measuring quality of care, providers tend to focus on only what they directly control or easily measured clinical indicators. However, measuring the full set of outcomes that matter to patients by condition is essential in meeting their needs.

And when outcomes are measured comprehensively, results invariably improve. Disutility of care or treatment process for instance, diagnostic errors, ineffective care, treatment-related discomfort, complications, adverse effects. Tier 2 outcomes relate to the nature of the care cycle and recovery. The level of discomfort during care and how long it takes to return to normal activities also matter greatly to patients. Significant delays before seeing a specialist for a potentially ominous complaint can cause unnecessary anxiety, while delays in commencing treatment prolong the return to normal life.

Even when functional outcomes are equivalent, patients whose care process is timely and free of chaos, confusion, and unnecessary setbacks experience much better care than those who encounter delays and problems along the way.

Tier 3 outcomes relate to the sustainability of health. It is also one of the most powerful vehicles for lowering health care costs. If Tier 1 functional outcomes improve, costs invariably go down. If any Tier 2 or 3 outcomes improve, costs invariably go down. By failing to consistently measure the outcomes that matter, we lose perhaps our most powerful lever for cost reduction. Over the past half dozen years, a growing array of providers have begun to embrace true outcome measurement.

Many of the leaders have seen their reputations—and market share—improve as a result. A welcomed competition is emerging to be the most comprehensive and transparent provider in measuring outcomes. The Cleveland Clinic is one such pioneer, first publishing its mortality data on cardiac surgery and subsequently mandating outcomes measurement across the entire organization. The range of outcomes measured remains limited, but the Clinic is expanding its efforts, and other organizations are following suit.

At the individual IPU level, numerous providers are beginning efforts. Providers are improving their understanding of what outcomes to measure and how to collect, analyze, and report outcomes data. For example, some of our colleagues at Partners HealthCare in Boston are testing innovative technologies such as tablet computers, web portals, and telephonic interactive systems for collecting outcomes data from patients after cardiac surgery or as they live with chronic conditions such as diabetes.

Outcomes are also starting to be incorporated in real time into the process of care, allowing providers to track progress as they interact with patients. To accelerate comprehensive and standardized outcome measurement on a global basis, we recently cofounded the International Consortium for Health Outcomes Measurement. ICHOM develops minimum outcome sets by medical condition, drawing on international registries and provider best practices.

It brings together clinical leaders from around the world to develop standard outcome sets, while also gathering and disseminating best practices in outcomes data collection, verification, and reporting. Just as railroads converged on standard track widths and the telecommunications industry on standards to allow data exchange, health care providers globally should consistently measure outcomes by condition to enable universal comparison and stimulate rapid improvement.

For a field in which high cost is an overarching problem, the absence of accurate cost information in health care is nothing short of astounding. Few clinicians have any knowledge of what each component of care costs, much less how costs relate to the outcomes achieved. In most health care organizations there is virtually no accurate information on the cost of the full cycle of care for a patient with a particular medical condition.

Instead, most hospital cost-accounting systems are department-based, not patient-based, and designed for billing of transactions reimbursed under fee-for-service contracts. In a world where fees just keep going up, that makes sense. Existing systems are also fine for overall department budgeting, but they provide only crude and misleading estimates of actual costs of service for individual patients and conditions.

For example, cost allocations are often based on charges, not actual costs. As health care providers come under increasing pressure to lower costs and report outcomes, the existing systems are wholly inadequate.

Existing costing systems are fine for overall department budgeting, but they provide only crude and misleading estimates of actual costs of service for individual patients and conditions.

To determine value, providers must measure costs at the medical condition level, tracking the expenses involved in treating the condition over the full cycle of care. Then the cost of caring for a condition can be compared with the outcomes achieved. While rarely used in health care to date, it is beginning to spread. Where TDABC is being applied, it is helping providers find numerous ways to substantially reduce costs without negatively affecting outcomes and sometimes even improving them.

In light of those cost differences, focusing the time of the most expensive staff members on work that utilizes their full skill set is hugely important. Without understanding the true costs of care for patient conditions, much less how costs are related to outcomes, health care organizations are flying blind in deciding how to improve processes and redesign care.

Clinicians and administrators battle over arbitrary cuts, rather than working together to improve the value of care. Neither of the dominant payment models in health care—global capitation and fee-for-service—directly rewards improving the value of care. It also decouples payment from what providers can directly control. Fee-for-service couples payment to something providers can control—how many of their services, such as MRI scans, they provide—but not to the overall cost or the outcomes.

Providers are rewarded for increasing volume, but that does not necessarily increase value. The payment approach best aligned with value is a bundled payment that covers the full care cycle for acute medical conditions, the overall care for chronic conditions for a defined period usually a year , or primary and preventive care for a defined patient population healthy children, for instance.

Well-designed bundled payments directly encourage teamwork and high-value care. Payment is tied to overall care for a patient with a particular medical condition, aligning payment with what the team can control. Providers benefit from improving efficiency while maintaining or improving outcomes. Sound bundled payment models should include: severity adjustments or eligibility only for qualifying patients; care guarantees that hold the provider responsible for avoidable complications, such as infections after surgery; stop-loss provisions that mitigate the risk of unusually high-cost events; and mandatory outcomes reporting.

Governments, insurers, and health systems in multiple countries are moving to adopt bundled payment approaches. For example, the Stockholm County Council initiated such a program in for all total hip and knee replacements for relatively healthy patients.

The result was lower costs, higher patient satisfaction, and improvement in some outcomes. In Germany, bundled payments for hospital inpatient care—combining all physician fees and other costs, unlike payment models in the U. Among the features of the German system are care guarantees under which the hospital bears responsibility for the cost of rehospitalization related to the original care.

Here, mandatory outcomes reporting has combined with bundles to reinforce team care, speed diffusion of innovation, and rapidly improve outcomes. Providers that adopted bundle approaches early benefitted. Employers are also embracing bundled payments. The hospitals are reimbursed for the care with a single bundled payment that includes all physician and hospital costs associated with both inpatient and outpatient pre- and post-operative care.

Employees bear no out-of-pocket costs for their care—travel, lodging, and meals for the patient and a caregiver are provided—as long as the surgery is performed at one of the centers of excellence. The program is in its infancy, but expectations are that Walmart and other large employers will expand such programs to improve value for their employees, and will step up the incentives for employees to use them. Sophisticated employers have learned that they must move beyond cost containment and health promotion measures, such as co-pays and on-site health and wellness facilities, and become a greater force in rewarding high-value providers with more patients.

As bundled payment models proliferate, the way in which care is delivered will be transformed. For example, many hospitals routinely have patients return to see the cardiac surgeon six to eight weeks after surgery, but out-of-town visits seem difficult to justify for patients with no obvious complications.

In deciding to drop those visits, clinicians realized that maybe local patients do not need routine postoperative visits either. Providers remain nervous about bundled payments, citing concerns that patient heterogeneity might not be fully reflected in reimbursements, and that the lack of accurate cost data at the condition level could create financial exposure.

Those concerns are legitimate, but they are present in any reimbursement model. Providers will adopt bundles as a tool to grow volume and improve value. A large and growing proportion of health care is provided by multisite health care delivery organizations. Those proportions are even higher today. Unfortunately, most multisite organizations are not true delivery systems, at least thus far, but loose confederations of largely stand-alone units that often duplicate services.

There are huge opportunities for improving value as providers integrate systems to eliminate the fragmentation and duplication of care and to optimize the types of care delivered in each location. To achieve true system integration, organizations must grapple with four related sets of choices: defining the scope of services, concentrating volume in fewer locations, choosing the right location for each service line, and integrating care for patients across locations.

Is relocating service lines on the table? A starting point for system integration is determining the overall scope of services a provider can effectively deliver—and reducing or eliminating service lines where they cannot realistically achieve high value.

For community providers, this may mean exiting or establishing partnerships in complex service lines, such as cardiac surgery or care for rare cancers. For academic medical centers, which have more heavily resourced facilities and staff, this may mean minimizing routine service lines and creating partnerships or affiliations with lower-cost community providers in those fields. Although limiting the range of service lines offered has traditionally been an unnatural act in health care—where organizations strive to do everything for everyone—the move to a value-based delivery system will require those kinds of choices.

Second, providers should concentrate the care for each of the conditions they do treat in fewer locations. Concentrating volume is essential if integrated practice units are to form and measurement is to improve. Numerous studies confirm that volume in a particular medical condition matters for value.

Providers with significant experience in treating a given condition have better outcomes, and costs improve as well. Patients, then, are often much better off traveling longer distance to obtain care at locations where there are teams with deep experience in their condition. That often means driving past the closest hospitals. Organizations that progress rapidly in adopting the value agenda will reap huge benefits, even if regulatory change is slow.

Concentrating volume is among the most difficult steps for many organizations, because it can threaten both prestige and physician turf. Yet the benefits of concentration can be game-changing. In , the city of London set out to improve survival and prospects for stroke patients by ensuring that patients were cared for by true IPUs—dedicated, state-of-the-art teams and facilities including neurologists who were expert in the care of stroke.

These were called hyper-acute stroke units, or HASUs. At the time, there were too many hospitals providing acute stroke care in London 32 of them to allow any to amass a high volume. UCL Partners, a delivery system comprising six well-known teaching hospitals that serve North Central London, had two hospitals providing stroke care—University College London Hospital and the Royal Free Hospital—located less than three miles apart.

University College was selected to house the new stroke unit. Neurologists at Royal Free began practicing at University College, and a Royal Free neurologist was appointed as the overall leader of the stroke program.

These steps sent a strong message that UCL Partners was ready to concentrate volume to improve value. The number of stroke cases treated at University College climbed from about in to more than 1, in All stroke patients can now undergo rapid evaluation by highly experienced neurologists and begin their recovery under the care of nurses who are expert in preventing stroke-related complications.

The third component of system integration is delivering particular services at the locations at which value is highest. Less complex conditions and routine services should be moved out of teaching hospitals into lower-cost facilities, with charges set accordingly. There are huge value improvement opportunities in matching the complexity and skills needed with the resource intensity of the location, which will not only optimize cost but also increase staff utilization and productivity.

More recently, the hospital applied the same approach to simple hypospadias repairs, a urological procedure. Relocating such services cut costs and freed up operating rooms and staff at the teaching hospital for more-complex procedures. In many cases, current reimbursement schemes still reward providers for performing services in a hospital setting, offering even higher payments if the hospital is an academic medical center—another example of how existing reimbursement models have worked against value.

But the days of charging higher fees for routine services in high-cost settings are quickly coming to an end. The final component of health system integration is to integrate care for individual patients across locations.

Care should be directed by IPUs, but recurring services need not take place in a single location. For example, patients with low back pain may receive an initial evaluation, and surgery if needed, from a centrally located spine IPU team but may continue physical therapy closer to home. Wherever the services are performed, however, the IPU manages the full care cycle.

Integrating mechanisms, such as assigning a single physician team captain for each patient and adopting common scheduling and other protocols, help ensure that well-coordinated, multidisciplinary care is delivered in a cost-effective and convenient way. Health care delivery remains heavily local, and even academic medical centers primarily serve their immediate geographic areas.

If value is to be substantially increased on a large scale, however, superior providers for particular medical conditions need to serve far more patients and extend their reach through the strategic expansion of excellent IPUs. Buying full-service hospitals or practices in new geographic areas is rarely the answer.

Geographic expansion should focus on improving value, not just increasing volume. Geographic expansion takes two principle forms.

The first is a hub-and-spoke model. For each IPU, satellite facilities are established and staffed at least partly by clinicians and other personnel employed by the parent organization. In the most effective models, some clinicians rotate among locations, which helps staff members across all facilities feel they are part of the team.

As expansion moves to an entirely new region, a new IPU hub is built or acquired. Patients often get their initial evaluation and development of a treatment plan at the hub, but some or much care takes place at more-convenient and cost-effective locations.

Satellites deliver less complicated care, with complex cases referred to the hub.

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